What the Data for This Category Looks Like
Data for this category originates from formula systems, raw material batch ledgers, internal mixers, Mooney viscometers, rheometers, vulcanizers, and laboratory testing equipment. Daily generated documents include formula sheets, weighing records, mixing curves, rapid rubber property test reports, vulcanization process cards, mold usage records, and finished product performance reports. Data updates occur per raw material batch, per production batch, and per vulcanization cycle. Document fields include rubber species ratio, weighing weight, mixing temperature and duration, vulcanization mold temperature, holding time, pressure parameters, and test values. Common units are kilograms, degrees Celsius, minutes, and megapascals.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
High-frequency, small-batch data updates require tool calling to adapt to trigger rhythms ranging from milliseconds to minutes. This prevents production flow blockages caused by excessive waiting time. Mixed calls for multiple types of structured documents require plugins to pre-set field mapping rules for corresponding documents. This avoids cross-document field confusion. Precise traceability requirements for each batch and cycle require tool calling to bind the unique identifier of the corresponding batch. This ensures cross-review results are tied to specific production stages. The irreversible nature of vulcanization processes requires tool call verification results to synchronously block the flow of abnormal parameters. This prevents unqualified rubber compounds from entering subsequent production steps.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to dynamic calling requirements for multiple types of technical documents |
| Tool call trigger timing | Trigger at production batch nodes | Matches data update rhythms for each raw material batch, production batch, and vulcanization cycle |
| Maximum number of documents per single call | Top 8 | Fits the volume of documents generated per single production batch |
| Verification response timeout threshold | 25–35 seconds | Prevents blocking of real-time production flows |
| Field mapping rules | Bind category-specific document templates | Matches exclusive fields and units for formula sheets, vulcanization process cards, and similar documents |
| Workflow/API function-call configuration | Enable strict mode | Ensures only preconfigured compliant tools are called, preventing parameter out-of-bounds |
This configuration applies to FastGPT v4.17.0.
Three Common Misconfigurations
- Symptom: Returns
400 InternalError.Algo.InvalidParametererror, indicating abnormal tool parameter format. Cause: Fails to bind category-specific field mapping rules, and passes document fields from other categories to the current plugin. - Symptom: Plugins created online do not take effect in the workflow, and verification logic cannot be called. Cause: Fails to bind the published plugin to the workflow node, or fails to enable
functionCallstrict mode, resulting in the plugin not being triggered. - Symptom: Image parsing tool calls fail, and mixing curve image data cannot be read. Cause: Fails to adapt to category-specific image formats, or fails to configure calling parameters for the corresponding model, resulting in inability to parse curve images exported by internal mixers.
How to Confirm Successful Configuration
- Trigger a simulated production batch node, and check the tool call log to confirm the plugin is normally invoked.
- Pass typical document data from a single production batch, and verify whether the tool's returned verification results match category-specific field rules.
- Check the plugin's call response duration to confirm it falls within the preset timeout threshold range.
- Verify the abnormal parameter trigger logic, and confirm that blocking prompts are triggered in abnormal scenarios.
The values provided here are common starting points, and should be evaluated against the reader's own samples.